Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the ...Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the physiological monitoring of patients in the hospital environment and the daily monitoring at home.Although many target detection methods of UWB through-wall radar based on machine learning have been proposed,there is a lack of an opensource dataset to evaluate the performance of the algorithm.This published dataset is measured by impulse radio UWB(IR-UWB)through-wall radar system.Three test subjects are measured in different environments and several defined motion status.Using the presented dataset,we propose a human-motion-status recognition method using a convolutional neural network(CNN),and the detailed dataset partition method and the recognition process flow are given.On the well-trained network,the recognition accuracy of testing data for three kinds of motion status is higher than 99.7%.The dataset presented in this paper considers a simple environment.Therefore,we call on all organizations in the UWB radar field to cooperate to build opensource datasets to further promote the development of UWB through-wall radar.展开更多
In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can b...In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can be used to monitor the status and the location information of human targets behind the wall.However,the detection is out of order when classical MUSIC al-gorithm is applied to estimate the direction of arrival.In order to solve the problem,a time-fre-quency associated MUSIC algorithm suitable for through-wall detection and based on S-band stepped frequency continuous wave(SFCW)radar is researched.By associating inverse fast Fouri-er transform(IFFT)algorithm with MUSIC algorithm,the power enhancement of the target sig-nal is completed according to the distance calculation results in the time domain.Then convert the signal to the frequency domain for direction of arrival(DOA)estimation.The simulations of two-dimensional human target detection in free space and the processing of measured data are com-pleted.By comparing the processing results of the two algorithms on the measured data,accuracy of DOA estimation of proposed algorithm is more than 75%,which is 50%higher than classical MUSIC algorithm.It is verified that the distance and angle of human target can be effectively de-tected via proposed algorithm.展开更多
The imaging problem of low signal to noise ratio （SNR）echo is very important for ultra-wide band （UWB） through-wall radar. An improved multi-channel blind image restoration algorithm based on sub-space and constra...The imaging problem of low signal to noise ratio （SNR）echo is very important for ultra-wide band （UWB） through-wall radar. An improved multi-channel blind image restoration algorithm based on sub-space and constrained least square （CLS） is presented and applied to UWB radar system to deal with this issue. The high resolution of radar image is equivalent to multi-channel blind image restoration based on the improved model of the through-wall radar echo. And a new cost function is proposed to the multi-channel blind image restoration by considering the concept of sub-space as the limitation of blur identification. The proposed algorithm has all advantages of CLS and sub-space, and converts the image estimation to alternating-minimizing the two cost functions. Experimental results prove that the proposed algorithm is effective at improving the resolution of radar image even at low SNR.展开更多
将时间反转(Time Reversal,TR)技术与阵列成像技术相结合,通过数值仿真研究了该技术在超宽带穿墙雷达(Through-the-Wall-Radar,TWR)探测中的应用。仿真分别考虑了单层和多层墙体环境下隐蔽的单目标和多目标探测问题,并将相应的时间反转...将时间反转(Time Reversal,TR)技术与阵列成像技术相结合,通过数值仿真研究了该技术在超宽带穿墙雷达(Through-the-Wall-Radar,TWR)探测中的应用。仿真分别考虑了单层和多层墙体环境下隐蔽的单目标和多目标探测问题,并将相应的时间反转成像与改进的后向投影(Improved Back Projection,IBP)算法成像进行了对比。结果显示,时间反转技术能够为超宽带穿墙雷达探测系统提供更高分辨率的探测结果。展开更多
This paper firstly analyzes the property of the low frequency electromagnetic wave, which can penetrate many types of non-metallic materials, and the ability of Ultra-Wide Band (UWB) impulse signal which has high rang...This paper firstly analyzes the property of the low frequency electromagnetic wave, which can penetrate many types of non-metallic materials, and the ability of Ultra-Wide Band (UWB) impulse signal which has high range resolution. Then the methods are discussed for conducting surveillance through walls, detecting and locating the moving persons behind the partitions. The schematic diagram of Through-Wall Detecting Radar (TWDR) and the models of moving target are shown and the principle of detecting the moving target is also provided with coherent superimposing technique on a range gate. Finally an algorithm for estimating the location of targets is given. The performance of TWDR is validated by the experiments of penetrating a wood block, a red brick wall and a reinforced concrete wall.展开更多
基金This work was supported by the National Key Research and Development Program of China(2018YFC0810202)the National Defence Pre-research Foundation of China(61404130119).
文摘Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the physiological monitoring of patients in the hospital environment and the daily monitoring at home.Although many target detection methods of UWB through-wall radar based on machine learning have been proposed,there is a lack of an opensource dataset to evaluate the performance of the algorithm.This published dataset is measured by impulse radio UWB(IR-UWB)through-wall radar system.Three test subjects are measured in different environments and several defined motion status.Using the presented dataset,we propose a human-motion-status recognition method using a convolutional neural network(CNN),and the detailed dataset partition method and the recognition process flow are given.On the well-trained network,the recognition accuracy of testing data for three kinds of motion status is higher than 99.7%.The dataset presented in this paper considers a simple environment.Therefore,we call on all organizations in the UWB radar field to cooperate to build opensource datasets to further promote the development of UWB through-wall radar.
文摘In this paper,a time-frequency associated multiple signal classification(MUSIC)al-gorithm which is suitable for through-wall detection is proposed.The technology of detecting hu-man targets by through-wall radar can be used to monitor the status and the location information of human targets behind the wall.However,the detection is out of order when classical MUSIC al-gorithm is applied to estimate the direction of arrival.In order to solve the problem,a time-fre-quency associated MUSIC algorithm suitable for through-wall detection and based on S-band stepped frequency continuous wave(SFCW)radar is researched.By associating inverse fast Fouri-er transform(IFFT)algorithm with MUSIC algorithm,the power enhancement of the target sig-nal is completed according to the distance calculation results in the time domain.Then convert the signal to the frequency domain for direction of arrival(DOA)estimation.The simulations of two-dimensional human target detection in free space and the processing of measured data are com-pleted.By comparing the processing results of the two algorithms on the measured data,accuracy of DOA estimation of proposed algorithm is more than 75%,which is 50%higher than classical MUSIC algorithm.It is verified that the distance and angle of human target can be effectively de-tected via proposed algorithm.
基金Sponsored by the National Natural Science Foundation of China(60472110)
文摘The imaging problem of low signal to noise ratio （SNR）echo is very important for ultra-wide band （UWB） through-wall radar. An improved multi-channel blind image restoration algorithm based on sub-space and constrained least square （CLS） is presented and applied to UWB radar system to deal with this issue. The high resolution of radar image is equivalent to multi-channel blind image restoration based on the improved model of the through-wall radar echo. And a new cost function is proposed to the multi-channel blind image restoration by considering the concept of sub-space as the limitation of blur identification. The proposed algorithm has all advantages of CLS and sub-space, and converts the image estimation to alternating-minimizing the two cost functions. Experimental results prove that the proposed algorithm is effective at improving the resolution of radar image even at low SNR.
文摘将时间反转(Time Reversal,TR)技术与阵列成像技术相结合,通过数值仿真研究了该技术在超宽带穿墙雷达(Through-the-Wall-Radar,TWR)探测中的应用。仿真分别考虑了单层和多层墙体环境下隐蔽的单目标和多目标探测问题,并将相应的时间反转成像与改进的后向投影(Improved Back Projection,IBP)算法成像进行了对比。结果显示,时间反转技术能够为超宽带穿墙雷达探测系统提供更高分辨率的探测结果。
基金Supported by the National 863 Program (No.2001AA132020).
文摘This paper firstly analyzes the property of the low frequency electromagnetic wave, which can penetrate many types of non-metallic materials, and the ability of Ultra-Wide Band (UWB) impulse signal which has high range resolution. Then the methods are discussed for conducting surveillance through walls, detecting and locating the moving persons behind the partitions. The schematic diagram of Through-Wall Detecting Radar (TWDR) and the models of moving target are shown and the principle of detecting the moving target is also provided with coherent superimposing technique on a range gate. Finally an algorithm for estimating the location of targets is given. The performance of TWDR is validated by the experiments of penetrating a wood block, a red brick wall and a reinforced concrete wall.
